“货到人”拣选系统订单排序优化

doi:10.3901/JME.2016.04.206

摘要/Abstract

摘要： “货到人”拣选系统采用“出库-拣选-回库”的拣选模式,货箱出入库频率高成为制约拣选效率的关键。为降低货箱出入库频率,进而提高系统拣选效率,提出订单排序优化模型。定义订单耦合因子表示两个订单之间可放置于拣选缓存中的共用货箱数量,并以此作为模型参数,将优化目标由提高拣选效率转化为降低货箱出入库频率。模型中,每个拣选台内的订单排序优化问题可归结为旅行商(Tranvelling salesman problem, TSP)问题。为求解模型,提出改进的K-Means聚类算法。计算每个订单与其他订单间的耦合因子,并对其进行排序;以单拣选台所有订单的耦合因子之和最大为目标,为每个拣选台分配订单并对订单进行排序。仿真结果显示,优化后系统拣选效率提高15.9%。

关键词: 订单排序, 货到人, 拣选, 聚类, 耦合

Abstract: The “part-to-picker” picking system always adopts the picking mode described as “Out Stock-Picking-In Stock”, the key factor to restraint the picking efficiency is the frequency of “In-Out Stock”. The order sequence optimization model is proposed to decrease the frequency of “In-Out Stock” and improve the picking efficiency of the system. The order coupled factor is defined to represent the number of common SKU asked by two orders and can be placed in the temporary storage location. The model is built for order sequence optimization problem with the order coupled factor. In this model, the optimization object is transferred from improving picking efficiency to decreasing the frequency of “In-Out Stock”. The order sequence optimization problem in each picking station can be classified to the travelling salesman problem(TSP). An improved K-Means clustering algorithm is designed to solve the model. First, the coupled factor is calculated and sorted; then the orders is assigned to each picking station and sequenced to minimized the summation of the coupled factor of all orders. It is shown by the simulation that the picking efficiency can be improved by 15.9%.

Key words: clustering, coupled, order sequence, part-to-picker, picking

中图分类号:

F253

吴颖颖, 孟祥旭, 王艳艳, 胡金昌. “货到人”拣选系统订单排序优化[J]. 机械工程学报, 2016, 52(4): 206-210.

WU Yingying, MENG Xiangxu, WANG Yanyan, HU Jinchang. Order Sequence Optimization for “part-to-picker” Order Picking System[J]. Journal of Mechanical Engineering, 2016, 52(4): 206-210.

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